Baoping Xiong

Fujian University of Technology, Fuzhou University

Papers

Total Citations

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About

Baoping Xiong is a leading researcher in biomechatronics and intelligent rehabilitation engineering, whose work bridges the gap between human motion analysis and robotic control. His primary research areas include human joint moment prediction, exoskeleton robot control, and artificial neural network (ANN) applications in biomechanics. Xiong’s most significant contribution is pioneering an ANN-based approach for intelligent prediction of lower extremity joint moments, which eliminates the need for cumbersome kinetic data measurement—a breakthrough that enables real-time, non-invasive rehabilitation assessment and exoskeleton control. His foundational 2019 paper on this topic has garnered 58 citations, underscoring its impact on the field. In a subsequent 2020 study (18 citations), he advanced the methodology by systematically determining online measurable input variables grounded in the Hill muscle model, addressing a critical challenge in deploying ANN models for practical human-robot interaction. Xiong’s work is notable for its translational potential: by simplifying input requirements, his methods make exoskeleton systems more accessible for clinical and home-based rehabilitation. His research continues to shape the future of intelligent assistive technologies, offering scalable solutions for quantitative gait analysis and adaptive robotic support.